Representing and rendering dynamic scenes has been an important but challenging task.
Especially to accurately model complex motions high efficiency is usually hard to guarantee …

Implicit neural representation has paved the way for new approaches to dynamic scene
reconstruction. Nonetheless cutting-edge dynamic neural rendering methods rely heavily on …

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …

We introduce GaussianAvatars a new method to create photorealistic head avatars that are
fully controllable in terms of expression pose and viewpoint. The core idea is a dynamic 3D …

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem.
Despite recent advancements simultaneously achieving high-resolution photorealistic …

This paper aims to tackle the problem of modeling dynamic urban streets for autonomous
driving scenes. Recent methods extend NeRF by incorporating tracked vehicle poses to …

Representing human performance at high-fidelity is an essential building block in diverse
applications, such as film production, computer games or videoconferencing. To close the …

Abstract Constructing photo-realistic Free-Viewpoint Videos (FVVs) of dynamic scenes from
multi-view videos remains a challenging endeavor. Despite the remarkable advancements …

Abstract We introduce Gaussian-Flow a novel point-based approach for fast dynamic scene
reconstruction and real-time rendering from both multi-view and monocular videos. In …

Accurately and efficiently modeling dynamic scenes and motions is considered so
challenging a task due to temporal dynamics and motion complexity. To address these …